Throughout these experiments, we fixed the number of steps of the MH sampler (Algorithm REF ) to two, which has the added advantage of reducing the computational cost of evaluating proposals. The constraint level was determined by a grid search targeting cross-validation accuracy. As shown in Table REF , in both transformation sets considered, we find that our approach improves or closely matches existing approaches. The failure to achieve large improvements in accuracy over baselines, which has been attributed to a stagnation in data augmentation research [1]}, can also reflect the limits of the benchmarking setup.
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